Social Network Analysis of the Academic GIScience Community
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract There is mounting interest among scientists regarding the use of scientometric social network analysis, or quantitative analysis of the evolution of science as defined by individual researchers and the networks they form. Given that geographers have seldom used this approach compared to researchers in other fields, its implications for research and policy need to be assessed. We applied scientometric social network analysis to geographic information science (GIScience) to understand how the field has evolved over the last sixteen years and to assess the applicability of the standard logistic model of the growth of scientific disciplines. In particular, we examined collaboration in the field at multiple scales, namely, the evolution of the entire research network structure, the nature of subnetworks in defining geographic information science, and the roles individuals play within the community. By delineating how collaborations and research networks have evolved in GIScience, the study addresses the potential of scientometric social network analysis for geography. Existe un creciente interés entre los científicos sobre el uso del análisis cienciométrico de redes sociales, o análisis cuantitativo de la evolución de la ciencia según se defina ésta por investigadores individuales, y las redes que ellos forman. Tomando en cuenta que los geógrafos rara vez han utilizado este enfoque, en comparación con lo que hacen investigadores de otros campos, es necesario evaluar sus implicaciones para investigación y política. Aplicamos el análisis cienciométrico de redes sociales en ciencia de la información geográfica (GIScience, en inglés) para entender cómo ha evolucionado el campo durante los pasados dieciseis años y para evaluar la aplicabilidad del modelo logístico estándar del crecimiento de las disciplinas científicas. En particular, examinamos la colaboración en el campo a escalas múltiples, o sea la evolución de la estructura de la red de investigación completa, la naturaleza de subredes para definir la ciencia de la información geográfica, y los papeles que juegan los individuos en la comunidad. Al delinear cómo han evolucionado las colaboraciones y las redes de investigación en GIScience, el estudio aboca el potencial que tiene el análisis cienciométrico de redes sociales para la geografía. Key Words: coauthorship networkGIScience communityscientometric social network analysis关键词: 合著著作权网络地理信息科学界科学计量社会网络分析Palabras clave: redes de coautoríacomunidad de GIScienceanálisis cienciométrico de redes sociales Acknowledgments SHIPENG SUN is a Postdoctoral Fellow in the School of Planning, Faculty of Environment at the University of Waterloo, 200 University Avenue West, Waterloo, ON N2L3G1, Canada. E-mail: s27sun@uwaterloo.ca. His research interests include network analysis, agent-based modeling, intraurban migration, and land use change. STEVEN M. MANSON is an Associate Professor in the Department of Geography, University of Minnesota, 267 19th Avenue South, Minneapolis, MN 55414. E-mail: manson@umn.edu. His research interests include environmental science, socio-theoretic frameworks, computational modeling, and GIScience. Notes *This work is supported in part by the National Aeronautics and Space Administration New Investigator Program in Earth-Sun System Science (NNX06AE85G) and the University of Minnesota. The authors gratefully acknowledge the efforts of the editor, anonymous reviewers, HEGIS Lab personnel, and members of the AAG Spatial Analysis and Modeling group presented with an early iteration of this research. Responsibility for the opinions expressed herein is solely that of the authors.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it